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A Multi-Sensor-Based Terrain Perception Model for Locomotion Selection of Hybrid Mobile Robots

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Abstract

Autonomous mobile robots can travel and perform activities without human involvement. These robots are outfitted with various sensors, actuators, and onboard computing capabilities to detect their environment, make decisions, and execute tasks independently. The performance of such robots depends on how well they perceive their environments. Most sensors are employed towards the surroundings for decision-making and path planning. This paper tries a different approach that complements environment perception to increase the robot’s perception ability. The suggested approach uses standard sensors like cameras, light sensors, distance sensors, accelerometers, and gyroscope sensors in a compact sensor box meant to face the ground to provide terrain perception ability to the robots. The sensor box uses a supervised learning-based concept to categorize different types of terrain and estimate how practicable they are in terms of percentage, i.e., the terrain perception percentage. The experimental outcomes depict that the terrain perception model gives a reliable indication of the practicability of terrains, thereby increasing the perception abilities of robots.

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The presented manuscript has no associated data and does not contemplate future depositions.

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Acknowledgements

This article has not been submitted to any of the journals and conferences anywhere before.

Funding

This work was supported by REVA University, Bangalore, INDIA under the University seed funding granted on 28-02-2022 [Grant No: RU:EST:EC:2022/41].

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Authors and Affiliations

  1. School of Electronics and Communication Engineering, REVA University, Bengaluru, Karnataka, 560064, India

    Kouame Yann Olivier Akansie, Rajashekhar C. Biradar & R. Karthik

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  1. Kouame Yann Olivier Akansie
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  2. Rajashekhar C. Biradar
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  3. R. Karthik
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All authors contributed to the write-up of the paper. Kouame Yann Olivier Akansie wrote the first and final drafts of the manuscript, and all authors commented on previous versions. All authors read and approved the final manuscript.

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Correspondence to Kouame Yann Olivier Akansie.

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This article is part of the topical collection “Advances in Computational Approaches for Image Processing, Wireless Networks, Cloud Applications and Network Security” guest edited by P. Raviraj, Maode Ma and Roopashree H R.

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Akansie, K.Y.O., Biradar, R.C. & Karthik, R. A Multi-Sensor-Based Terrain Perception Model for Locomotion Selection of Hybrid Mobile Robots. SN COMPUT. SCI. 5, 512 (2024). https://doi.org/10.1007/s42979-024-02858-6

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